Global AI Regulations Compared: EU, US, China Face Compliance Gaps

A new comparative review analyzes AI regulations across the EU, US, and China, focusing on high-risk use cases and the operationalization of FAIR principles. The study highlights recurring gaps in interoperability mandates, the integration of AI with sector-specific and data protection regulations, and governance for critical digital infrastructure. To address these challenges, the paper proposes Knowledge Blocks, a machine-checkable compliance artifact pattern using RDF/OWL, SHACL, and PROV-O, designed to facilitate audit-ready compliance-by-design across different regulatory regimes. AI

IMPACT Provides a framework for navigating complex global AI regulations, potentially streamlining compliance for AI operators.

RANK_REASON The item is an academic paper presenting a comparative review of AI regulations and proposing a new compliance artifact pattern. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

• Aasish Kumar Sharma
• central bank digital currency
• China
• electroencephalography
• EU
• Fair
• graphics processing unit
• PROV-O: The PROV Ontology
• Rdf Owl
• SHACL
• US

• policy
• paper

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